Synthetic biology aims to design biological systems with specific functions, often optimizing existing capabilities or creating new ones. However, current designs often fail in real-world applications due to complexity and limited innovation. This article proposes an open-ended approach to biological design, where novelty is as important as functionality. By embracing novelty, synthetic biology can move beyond diminishing returns and generate innovative solutions. Research in artificial life shows that novelty can lead to unexpected solutions beyond local optima. Synthetic biology offers a unique opportunity to explore creative design approaches. The natural world demonstrates open-ended innovation through evolution, continuously generating novel proteins, metabolisms, and morphologies. Sociotechnical systems also exhibit open-endedness, with rapid technological and cultural advancements. Humans have long harnessed biology for various purposes, and recent advances in synthetic biology allow for precise engineering of living systems. This has enabled biology to act as a basis for technological innovation. Biological engineering differs from other engineering disciplines because biology can adapt and evolve. Unlike human-engineered machines, biological systems are self-organizing and robust to change. They also lack the hardware-software duality found in human-made systems. The ability for biology to evolve is both a blessing and a curse for synthetic biology. Directed evolution is a routine tool in biotechnology for optimizing biological components. However, recent work advocates for a broader integration of evolution in synthetic biology. Open-endedness is the capacity of a system to endlessly improve, produce novelty, or increase complexity. It is characterized by the absence of a clear goal. Open-ended processes are found in natural evolution, technological innovation, and the creation of art and fiction. Open-endedness is a major research topic in artificial life, with implications for AI and other fields. The open-ended nature of biological evolution is well established. Evolutionary processes can be classified based on the generation of new adaptations. Open-ended evolution is characterized by the continuous creation of new evolvable traits. Recent work has shown that complex microbial ecosystems in changing environments often exhibit open-ended regimes. Open-endedness is closely tied to the generation of novelty. Novelty is the degree to which an entity is new or unusual. It can be manifested in two ways: changes in the composition of the entity or changes in its behavior. Open-ended systems generate unlimited improvements and novelty, including evolvability, major transitions, and semantic evolution. Novelty, innovation, and creativity are essential for open-ended evolution. Creativity is the ability to generate new, unexpected, and potentially valuable entities. Artificial life researchers have explored computational creativity, with methods like genetic algorithms and deep learning showing promise. The reality gap problem highlights that entities evolved in simulated environments may not work well in real-life situations. The stepping stone problem indicates that intermediate steps in achieving a goal may not be obvious. These challenges are significant in synthetic biology, where systems are often developed in controlled lab conditions. Novelty-based search can alleviate both the reality gap and the stepping stone problem. By focusing on novelty andSynthetic biology aims to design biological systems with specific functions, often optimizing existing capabilities or creating new ones. However, current designs often fail in real-world applications due to complexity and limited innovation. This article proposes an open-ended approach to biological design, where novelty is as important as functionality. By embracing novelty, synthetic biology can move beyond diminishing returns and generate innovative solutions. Research in artificial life shows that novelty can lead to unexpected solutions beyond local optima. Synthetic biology offers a unique opportunity to explore creative design approaches. The natural world demonstrates open-ended innovation through evolution, continuously generating novel proteins, metabolisms, and morphologies. Sociotechnical systems also exhibit open-endedness, with rapid technological and cultural advancements. Humans have long harnessed biology for various purposes, and recent advances in synthetic biology allow for precise engineering of living systems. This has enabled biology to act as a basis for technological innovation. Biological engineering differs from other engineering disciplines because biology can adapt and evolve. Unlike human-engineered machines, biological systems are self-organizing and robust to change. They also lack the hardware-software duality found in human-made systems. The ability for biology to evolve is both a blessing and a curse for synthetic biology. Directed evolution is a routine tool in biotechnology for optimizing biological components. However, recent work advocates for a broader integration of evolution in synthetic biology. Open-endedness is the capacity of a system to endlessly improve, produce novelty, or increase complexity. It is characterized by the absence of a clear goal. Open-ended processes are found in natural evolution, technological innovation, and the creation of art and fiction. Open-endedness is a major research topic in artificial life, with implications for AI and other fields. The open-ended nature of biological evolution is well established. Evolutionary processes can be classified based on the generation of new adaptations. Open-ended evolution is characterized by the continuous creation of new evolvable traits. Recent work has shown that complex microbial ecosystems in changing environments often exhibit open-ended regimes. Open-endedness is closely tied to the generation of novelty. Novelty is the degree to which an entity is new or unusual. It can be manifested in two ways: changes in the composition of the entity or changes in its behavior. Open-ended systems generate unlimited improvements and novelty, including evolvability, major transitions, and semantic evolution. Novelty, innovation, and creativity are essential for open-ended evolution. Creativity is the ability to generate new, unexpected, and potentially valuable entities. Artificial life researchers have explored computational creativity, with methods like genetic algorithms and deep learning showing promise. The reality gap problem highlights that entities evolved in simulated environments may not work well in real-life situations. The stepping stone problem indicates that intermediate steps in achieving a goal may not be obvious. These challenges are significant in synthetic biology, where systems are often developed in controlled lab conditions. Novelty-based search can alleviate both the reality gap and the stepping stone problem. By focusing on novelty and